The integration of deep learning techniques and physics-driven designs is reforming the way we address inverse problems, in which accurate physical properties are extracted from complex observations.

The accurate description of deformed atomic nuclei by orbital-free density functional theory has been a longstanding textbook challenge, due to the difficulty in accounting for quantum shell effects.

Under cover The new transfer-learning system could be used to identify shipments of illicit nuclear materials. (Courtesy: Shutterstock/Gualtiero Boffi) Machine-learning could help us use cosmic muons ...

Please see the full solicitation for complete information about the funding opportunity. Below is a summary assembled by the Research & Innovation Office (RIO). The DOE SC program in Nuclear Physics ...